D4.3: Development of the Pitagoras monitoring platform · conversion and finally send the required...

D4.3: Development of the Pitagoras monitoring platform

Project acronym: PITAGORAS

Project full title: SUSTAINABLE URBAN PLANNING WITH INNOVATIVE AND LOW ENERGY THERMAL AND POWER GENERATION FROM RESIDUAL AND RENEWABLE SOURCES

Grant agreement no.: 314596

Doc. Ref.: PITAGORAS-WP4-Task4.3-D4.3-07-V0.3

Responsible: AIGUASOL

Author(s): AIGUASOL

Date of issue: 02/12/2016

Status: Final

Security: Public

Change control:

Version and date Changes

V0.1, 25/11/2016

V0.2, 30/11/2016

V0.3, 02/12/2016

1st draft for dissemination among task 4.3 partners

Review

Final

PITAGORAS-WP4-Task 4.3-D4.3-V0.1 D4.3: Development of the Pitagoras monitoring platform Date of issue: 02/12/2016

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TABLE OF CONTENTS

1 INTRODUCTION 1

2 MONITORING SYSTEM INFRASTRUCTURE 2

2.1 DATA STRUCTURE 3

2.2 DATA PRESENTATION SYSTEM 5

2.2.1 Welcome page 5

2.2.2 Authentication 5

2.2.3 Map 6

2.2.4 Installation sheet 7

2.2.5 Dashboard 8

2.3 DATA ANALYSIS SYSTEM 9

2.3.1 Historical Menu 9

3 METRICS 13

3.1 TECHNICAL INDICATORS 13

3.2 ENVIRONMENTAL INDICATORS 15

4 CONCLUSSIONS 16

5 REFERENCES 17


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List of figures

Figure 2.1: Monitoring system infrastructure. ________________________________________________________ 2 Figure 2.2: Conceptual structure of the Pitagoras monitoring platform deployed for the Brescia demonstration plant. ________________________________________________________________________________________ 3 Figure 2.3: Pitagoras monitoring platform Home page ________________________________________________ 5 Figure 2.4: Pitagoras monitoring platform Login page _________________________________________________ 6 Figure 2.5: Pitagoras monitoring platform Map page. _________________________________________________ 7 Figure 2.6: Pitagoras monitoring platform Card page. _________________________________________________ 7 Figure 2.7: One of the Dashbaords included in the Pitagoras monitoring platform. __________________________ 8 Figure 2.8: Dashboard editor for pitagoras-admin users. _______________________________________________ 9 Figure 2.9: Pitagoras monitoring platform Data Analysis section. ________________________________________ 9 Figure 2.10: Build your chart page, selecting variables. _______________________________________________ 10 Figure 2.11: Pitagoras monitoring platform Build you chart page. ______________________________________ 11 Figure 2.12: Build you chart page, statistics tab. ____________________________________________________ 11 Figure 2.13: Pitagoras monitoring platform Compare periods page. _____________________________________ 12 Figure 3.1: Technical KPIs dashboard _____________________________________________________________ 13


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LIST OF TABLES

Table 1 Technical Indicators ........................................................................................................................................ 13 Table 2 Environmental Indicators ............................................................................................................................... 15


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1 INTRODUCTION

This document is meant with the aim to describe the monitoring platform that has been deployed within the project according to the specifications established in deliverable D4.2 Implementation of monitoring devices and definition of the specifications of the Pitagoras monitoring platform [1].

The monitored platform has been developed for the demonstration plant in Brescia and is able to analyse and evaluate the performances of the different subsystems developed within the project, including the waste heat recovery system, the ORC unit and the thermal energy supply system. This assessment is obtained through some common parameters and ratios (metrics and KPI) that characterize the energy, environmental and economic behaviour of the energy system.

The structure of the proposed monitoring platform that has been implemented in the Brescia demo plant also guarantees the integration of the monitoring system and the existing data acquisition system to provide comprehensive data to the on-line observation software.

In Chapter 2 the final infrastructure designed is presented. Further, this chapter also pretends to bring the information necessary to be used as a user manual of the monitoring web platform (data presentation system). In particular will be described the following topics:

How this system exchange data with the data storage system

The data structure used to present data

How data are presented to the users

The security system used to ensure the security of sensitive information

The tools available to analyse the data

Chapter 3 presents the final metrics selected and implemented in order to evaluate the performances of the different subsystems.


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2 MONITORING SYSTEM INFRASTRUCTURE

The final architecture of the monitoring platform has been done according to the specifications established in the deliverable D4.2 Implementation of monitoring devices and definition of the specifications of the Pitagoras monitoring platform [1]. This chapter presents the final output of this infrastructure describing the prototype of the data analysis and presentation system deployed within the project. This is a web-based platform and contains the tools and interfaces developed to post process and present data stored from Brescia demo plant. The monitoring platform will be hosted by Aiguasol during the project.

Figure 2.1: Monitoring system infrastructure.

Some features of the web-based platform were taken from the web-based platform nrgAuditor developed by the company SIGE [2] and it has been necessary to parachute a software licence in order to use it. These features are the background for the platform developed in this task, as the structure of the platform and presentation services were maintained. However it has been necessary to develop some new and specific features for the project:

The database used in this project is a NoSQL database (OpenTSDB), instead of a typical Relational DB (MySQL).

Also an important work has been necessary in order to integrate the data acquisition system and the storage system. For instance, the binding between the existing SCADA system and the OpenTSDB;

The GUI has been customized for the Pitagoras project. New interfaces and new dashboards have been developed;

Menus, images and infographics enable the navigation among different areas sets and different tools. The structure of some pages and the navigation structure are better detailed in the next chapter.

Demo plant facility

Energy system

Monitoring System

SCADA of the plant

Cloud Infrastructure

NoSQL DB

Data acquisition and Storage System Data

Presentation System

www

Web client Web Service – Web API REST

POST Method GET Method Web-based

Platform

Mess 1

Mess 2

..

Windows Service


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2 .1 DATA STRUCTURE

As already mentioned, the Brescia demo plant already has its own SCADA system that has been equipped with the requisite sensors to control the new process properly and to provide the necessary monitoring data in the required accuracy. An important work has been necessary in order to guarantee the integration of the monitoring system and the existent data acquisition system. However this existent SCADA (demo plant side) doesn’t provide a Web Client able to send out the monitored data, so instead it has been necessary to develop a set of intermediate applications in order to extract the data from the pilot plant, perform a data conversion and finally send the required data to the Cloud Infrastructure, where is stored in the data base as time series. The figure bellows (Figure 2.2) shows the basic structure of the Pitagoras monitoring platform.

Figure 2.2: Conceptual structure of the Pitagoras monitoring platform deployed for the Brescia demonstration plant.

As already mentioned, the database used in Pitagoras is a NoSQL database (OpenTSDB), instead of a typical relational DB (MySQL [3]). Large monitoring systems generate large amounts of heterogeneous, semi-structured information. For this reason the server, the storage system and the network communications where all these data will be stored, processed and analysed have to be correctly designed and dimensioned. The best choice is the use of a NoSQL database. If the data acquired are only time series the choice falls on key-value or column-oriented databases like OpenTSDB [4] or InfluxDB [5].

OpenTSDB is a distributed storage system for managing structured data that is designed to scale to a very large size and consists of a Time Series Daemon (TSD) as well as set of command line utilities. Interaction with OpenTSDB is primarily achieved by running one or more of the TSDs. Each TSD is independent, thus there is no master, and no shared state so you can run as many TSDs as required to handle any load you throw at it.


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In addition, the use of this type of database also has some other advantages when handling and identify (name) the variables monitored. With OpenTSDB each time series can be identified with a combination of tag key/value pairs that allows for flexible queries with very fast aggregations.

The use of OpenTSDB also simplify the process to show the data in the data presentation system. Almost all the features are accessible via the API such as querying time series data, managing metadata and storing data points. The Query API Endpoint enables extracting data from the storage system. The request parameters include:

start: the start time for the query.

end: an end time for the query, if not supplied OpenTSDB will assume the current time.

queries: one or more sub queries to select the time series to return.

As mentioned, each sub query can performing aggregation or grouping calculations of each set. Fields for each sub query include:

aggregator: the name of an aggregation function to use.

rate: this is useful if you want to view the rate of change between data points.

downsample: a downsampling function to reduce the amount of data returned.

tag: to drill down to specific time series or group results by tag.

An example of query via HTTP API is this:

http://address:portnumber/api/query?arrays=true&start=startDate&end=endDate&m=sum:900s-avg:Metric{tag=...}

where:

array=true: Returns the data points formatted as an array of arrays instead of a map of key/value pairs. Each array consists of the timestamp followed by the value;

m=sum: Aggregation operator in the case of multiple data available with the same timestamp;

60s-avg: Range and type of temporal aggregation to be made;

Metric: used to specify which metric is requested for the query;

tag: List of tags related to the metric.

Finally, the data collected from the existing SCADA and stored in OpenTSDB as time series have been associated to the variables that are shown in the data presentation system. At this point, it has been also possible to create new variables joining values from more than one signal. For instance, in order to analyze the performance of the Brescia pilot plant, new analogic variables have been created to show some of the metrics identified in D4.4 [6]. In Chapter 3 the final KPIs implemented are presented.

In addition to the above, a secondary data base has also been implemented in order to store some relational data, mainly for internal purposes of the data presentation system. This time, a typical relational data base (MySQL) has been used. This DB also will be used for other secondary tasks like share information with the EMS, that has been implemented in the task T2.8 and will be validated in Task 4.7.


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2 .2 DATA PRESENTATION SY STEM

The monitoring web platform is accessible through the URL: http://pitagoras.aiguasol.coop. Although the logo and some other visual aspects are the same, it was not in the aim of this task to copy the look of the Pitagoras project site [7], since the monitoring web platform will be only available for internal use.

2 . 2 . 1 W e l c o m e p a g e

The homepage is characterized by a screen (Figure 2.3), where is shown the most important information related to the project.

Figure 2.3: Pitagoras monitoring platform Home page

Accessing to the homepage platform the user can see two tabs:

The Login tab that allows to the user to log in into the platform and see all the data and features for which he has permissions.

The Help tab that allows to download a brief overview with the main capabilities of the monitoring web platform, included as a user manual.

2 . 2 . 2 A u t h e n t i c a t i o n

The monitoring web platform uses membership providers in order to manage the data regarding a site's registered users, and to provide methods for creating users, deleting users, verifying login credentials and changing passwords. In this way the platform provides a good authentication system and provides good security on sensitive data, discriminating the information to show according to the type of user.

In the homepage by clicking on the login button it is possible to access to the “Login” page (Figure 2.4).

http://pitagoras.aiguasol.coop/


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Figure 2.4: Pitagoras monitoring platform Login page

The log in credentials are of two types:

pitagoras: This account allows the visualization of different sections of the platform (including the data analysis with graphs and tables).

pitagoras-admin: This account allows all the functionality of the guest account together with the possibility to edit and create new dashboards and charts.

Entering "Username" and "Password" it is possible to access personalized screens.

2 . 2 . 3 M a p

Once logged on, the first page the user can visualize by default is the “Location/Listing” section, where the location of the monitored facilities, available according with the corresponding account information, can be easily found using an interactive map or a list. Also, the different sections of the monitoring web platform, are available at the top of the page, as a selectable tabs.


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Figure 2.5: Pitagoras monitoring platform Map page.

On the interactive map, by clicking on the facility icon, it is possible to show the address of the facility and access to basic information about the installation on Card section (Figure 2.5).

2 . 2 . 4 I n s t a l l a t i o n s h e e t

In this section a brief overview of the selected installation can be displayed as well as its main parameters.

Figure 2.6: Pitagoras monitoring platform Card page.


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2 . 2 . 5 D a s h b o a r d

The “Dashboard” or “Real Time” section is divided into a series of screens, displayed at the top of selectable tabs to switch between pages. Each screen has its own title that introduces the specific content of the corresponding page and allows to view all the basic information of data measured.

Figure 2.7: One of the Dashbaords included in the Pitagoras monitoring platform.

The information is made available through widgets (summary indicators and shortcuts to preconfigured graphics) and may represent:

Measures directly acquired in real time (with an offset of one week) or trends historicized.

Information that is the result of formulas and logical operations.

Data entered manually.


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Figure 2.8: Dashboard editor for pitagoras-admin users.

In Pitagoras project dashboards have been organized in two main sections:

Schemes: in this section monthly mean measures (with an offset of one week) or trends historicized regarding to the main subsystems of the facility are shown.

KPIs: the final metrics selected and implemented in order to evaluate the performances of the different subsystems are shown in this section (see chapter 3).

2 .3 DATA ANALYSIS SYSTEM

The Analysis area ensures the access to the measured data stored and allows the users to visualize,

check, analyse and export the measured data collected from the monitored facilities.

2 . 3 . 1 H i s t o r i c a l M e n u

By clicking on the "Historical" button, availeble at the top of the page, the user can select the pages "Build

your chart" or “Compare periods”. Through these sections all data and records within the database can be

viewed, analysed and compared. The user can choose the type of chart to display and select from a

number of options and customisable parameters. These operations are discussed in this section.

Figure 2.9: Pitagoras monitoring platform Data Analysis section.


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Figure 2.9 shows the “Build your chart” page that allows to view and manage all the measurement data

collected and recorded within the database. By clicking on the first dropdown menu is possible to select

one of the facilities associated to the user profile and then visualized all the variables available in the

second menu. After selecting the desired variable is necessary to click the button “+Add” to display it. Once

selected the desired variable through the input area, the user can control and display the desired variable

(¡Error! No se encuentra el origen de la referencia.).

Figure 2.10: Build your chart page, selecting variables.

In detail, the input parameters are:

• Start: that represents the departure date of the interest period;

• End: it is the end date of the period of interest but will not be included in the extraction data.

• Time interval: is the method of aggregation of data in the database. The pre-selected item is "H" that

corresponds to a sample rate of one hour.

The chart displayed by the system is interactive so the user can apply the zoom by selecting with the

mouse certain portions of the graph, disable and unable a measurement by performing a simple click on

the legend item. The scales are automatically changed.


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Figure 2.11: Pitagoras monitoring platform Build you chart page.

Once plotted the chart it is possible to export the document as .xslx by clicking on the icon “Export” at the

lower right corner. Also there is a "Statistics" tab to view summary data for the entire data set with

reference to the period selected. The data shown correspond to the average of all the values of the series,

to the min value and the max value (Figure 2.12).

Figure 2.12: Build you chart page, statistics tab.

In the "Compare periods" page (Figure 2.13¡Error! No se encuentra el origen de la referencia.) can be

performed comparisons of the selected measurement with itself in other time periods.


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Figure 2.13: Pitagoras monitoring platform Compare periods page.


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3 METRICS

In this chapter the final metrics selected and implemented in order to evaluate the performances of the

different subsystems are presented. In Figure 3.1 an example of dashboard for the metrics is shown.

Figure 3.1: Technical KPIs dashboard

Task 4.4. of the PITAGORAS project works on defining the KPIs of the project. Technical, environmental, social and economic KPIs are being defined. The first version of the PITAGORAS monitoring platform includes the most relevant technical and environmental indicators:

Technical Indicators: where are included those KPIs which assess the performances from a technical point of view.

Environmental Indicators: where are included those KPIs which assess the performance related to the environmental impact.

3 .1 TECHNICAL INDICATORS

Table 1 shows the metrics selected to evaluate the technical performance of the facility.

Table 1 Technical Indicators

Name Definition Units

Average power (waste

heat)

Average power of recovered waste heat in the WHRU kW

Average maximum power

(waste heat)

Average maximum power of recovered waste heat in the WHRU kW


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Average minimum power

(waste heat)

Average minimum power of recovered waste heat in the WHRU kW

Recovered waste energy Recoverded waste heat in the WHRU. kWh

Average plant efficiency

(electricity mode)

Ratio between the net electricity output of the ORC and the waste

heat recovered in the WHRU

%

Average power (ORC) Average gross electric power output of the ORC. kW


(ORC)

Average maximum gross electric power output of the ORC. kW


(ORC)

Average minimum gross electric power output of the ORC. kW

Electricity generation

(ORC)

Net electricity produced by the ORC. kWh

Renewable energy ratio The degree of energetic self-supply is defined as ratio of locally

produced energy (electricity) and the local consumption (electricity

produced by the plant) over a period of time.

%

Average plant efficiency

(heating mode)

Ratio between the thermal energy delivered to the DH network and

the waste heat recovered in the WHRU

%

Average power (thermal

energy)

Average power of thermal energy supplied to the distric heating. kW


(thermal energy)

Average maximum power of thermal energy supplied to the distric

heating.

kW


(thermal energy)

Average minimum power of thermal energy supplied to the distric

heating.

kW

Thermal energy

production

Thermal energy supplied to the DH network kWh


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3 .2 ENVIRONMENTAL INDICATORS

Table 2 shows the metrics selected to evaluate the technical performance of the facility.

The following point should be considered: the pilot plant produces heat and electricity from waste heat, there is no

other energy consumped than waste heat. No impacts are considered for the waste heat, thus under this assumption

there are no environmental impacts associated to this plant and instead, avoided impacts are calculated.

Table 2 Environmental Indicators

Name Definition Units

Avoided Greenhouse gas

emissions

Avoided GHG emission due to the heat delivered to the DH (which

replaces the consumption of current energy sources in the network) and

due to the produced electricity (which avoids the electricity consumption

from the grid).

tonCO2

equ/yr

Avoided total Primary

Energy Consumption

Avoided total Primary Energy (PE) consumption due to the heat

delivered to the DH (which replaces the consumption of current energy

sources in the network) and due to the produced electricity (which

avoids the electricity consumption from the grid).

tonCO2

equ/yr

Avoided Primary Energy

consumption (non-

renewable part)

Avoided Primary Energy (PE) consumption considering only the non-renewable part. It is due to the heat delivered to the DH (which replaces the consumption of current energy sources in the network) and due to the produced electricity (which avoids the electricity consumption from the grid).

MWh/yr

Avoided CO2 emissions

Avoided CO2 emission due to the heat delivered to the DH (which

replaces the consumption of current energy sources in the network) and

due to the produced electricity (which avoids the electricity consumption

from the grid).

tonCO2 /yr


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4 CONCLUSSIONS

In this deliverable the developed monitoring platform has been presented. In particular in this document

how this system exchanges data with the data storage system, based Time Series Data Base, the data

structure used to presents data and how data are presented to the users have been described. The main

indicators developed to visualize instant values or metrics identified in Task 4.4. “Definition of Key

Performance Indicators for the developed Pitagoras concept” have been integrated within the platform.

These metrics are used to evaluate properly the performance of the Brescia pilot plant. The developed

platform will be a valuable tool for internal use for monitoring data analysis (Task 4.5.). The developed tool

will significantly reduce the necessary time and resources for monitoring data handling and analysis. It will

be used as well to get key information about the pilot plant performance which will be the input for the on-

going activity in WP5 and WP6.


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5 REFERENCES

[1] Pitagoras, "D4.2 Implementation of monitoring devices and definition of the specifications of the Pitagoras monitoring platform," 2016.

[2] SIGE, «SIGE web - Gestión Informática. Automatización y Control, Eficiencia Energética.,» 2013. [En línea]. Available: http://www.sige.es/.

[3] ORACLE, «MySQL web - The world's most popular open source database,» [En línea]. Available: https://www.mysql.com/.

[4] OpenTSDB, "OpenTSDB - A Distributed, Scalable Monitoring System," [Online]. Available: http://opentsdb.net/index.html.

[5] I. InfluxData, «InfluxDB - Time series data storage.,» 2016. [En línea]. Available: https://www.influxdata.com/time-series-platform/influxdb/.

[6] Pitagoras, «D4.4 Definition of Key Performance Indicators for the developed Pitagoras concept,» 2016.

[7] Pitagoras, «Pitagoras web,» 2014.. Available: http://pitagorasproject.eu/.

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